code: def test_maxpool(datadir):
      model = onnx.load(datadir.file("maxpool_2d.onnx"))
      net = load_onnx_neural_network(model)
      layers = list(net.layers)
      assert len(layers) == 4
      assert layers[1].activation == "relu"
      assert layers[2].activation == "linear"
      assert layers[3].activation == "linear"
      assert layers[1].kernel_shape == (2, 3)
      assert layers[2].kernel_shape == (1, 2)
      assert layers[3].kernel_shape == (4, 2)
      assert layers[1].strides == [1, 1]
      assert layers[2].strides == [1, 2]
      assert layers[3].strides == [3, 1]
      assert layers[1].output_size == [3, 5, 5]
      assert layers[2].output_size == [3, 5, 2]
      assert layers[3].output_size == [3, 2, 1]
      for layer in layers[1:]:
          assert layer.kernel_depth == 3
  
file_path: OMLT/tests/io/test_onnx_parser.py
imports: import pytest
  from omlt.dependencies import onnx, onnx_available
label_desc: Use image node_id 7 for calling a global function with example usage: test_maxpool(datadir) without return types